Open Graph Benchmark: Datasets for Machine Learning on Graphs

2 May 2020

Yuxiao Dong

Papers citing "Open Graph Benchmark: Datasets for Machine Learning on Graphs"

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Title
EGC2: Enhanced Graph Classification with Easy Graph Compression Jinyin Chen Haiyang Xiong Haibin Zheng Dunjie Zhang Jian Zhang Mingwei Jia Yi Liu AAML 32 15 0 16 Jul 2021
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning Paul Pu Liang Yiwei Lyu Xiang Fan Zetian Wu Yun Cheng ... Peter Wu Michelle A. Lee Yuke Zhu Ruslan Salakhutdinov Louis-Philippe Morency VLM 37 159 0 15 Jul 2021
Hierarchical graph neural nets can capture long-range interactions Ladislav Rampášek Guy Wolf 27 12 0 15 Jul 2021
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks Kaixiong Zhou Xiao Shi Huang Daochen Zha Rui Chen Li Li Soo-Hyun Choi Xia Hu GNN AI4CE 38 114 0 06 Jul 2021
Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction Jiahua Rao Shuangjia Zheng Yuedong Yang 21 46 0 01 Jul 2021
Bilinear Scoring Function Search for Knowledge Graph Learning Yongqi Zhang Quanming Yao James T. Kwok 4 19 0 01 Jul 2021
Edge Representation Learning with Hypergraphs Jaehyeong Jo Jinheon Baek Seul Lee Dongki Kim Minki Kang Sung Ju Hwang 24 64 0 30 Jun 2021
Edge Proposal Sets for Link Prediction Abhay Singh Qian Huang Sijia Huang Omkar Bhalerao Horace He Ser-Nam Lim Austin R. Benson 11 16 0 30 Jun 2021
Subgroup Generalization and Fairness of Graph Neural Networks Jiaqi Ma Junwei Deng Qiaozhu Mei 24 80 0 29 Jun 2021
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks Eli Chien Chao Pan Jianhao Peng O. Milenkovic GNN 49 129 0 24 Jun 2021
Visualizing Graph Neural Networks with CorGIE: Corresponding a Graph to Its Embedding Zipeng Liu Yangkun Wang J. Bernard T. Munzner 45 23 0 24 Jun 2021
Weisfeiler and Lehman Go Cellular: CW Networks Cristian Bodnar Fabrizio Frasca N. Otter Yu Guang Wang Pietro Lio Guido Montúfar M. Bronstein GNN 33 227 0 23 Jun 2021
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs Mikhail Galkin E. Denis Jiapeng Wu William L. Hamilton OCL 28 86 0 23 Jun 2021
GRAND: Graph Neural Diffusion B. Chamberlain J. Rowbottom Maria I. Gorinova Stefan Webb Emanuele Rossi M. Bronstein GNN 54 254 0 21 Jun 2021
Graph Context Encoder: Graph Feature Inpainting for Graph Generation and Self-supervised Pretraining Oriel Frigo Rémy Brossard David Dehaene 37 1 0 18 Jun 2021
Message Passing in Graph Convolution Networks via Adaptive Filter Banks Xing Gao Wenrui Dai Chenglin Li Junni Zou H. Xiong P. Frossard GNN 30 6 0 18 Jun 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 27 51 0 16 Jun 2021
Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks Meng Liu Cong Fu Xuan Zhang Limei Wang Yaochen Xie Hao Yuan Youzhi Luo Zhao Xu Shenglong Xu Shuiwang Ji GNN 11 17 0 16 Jun 2021
Optimizing Graph Transformer Networks with Graph-based Techniques Loc Hoang U. Agarwal G. Gill Roshan Dathathri Abhik Seal Brian Martin K. Pingali GNN 41 0 0 16 Jun 2021
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track Chengxuan Ying Mingqi Yang Shuxin Zheng Guolin Ke Shengjie Luo Tianle Cai Chenglin Wu Yuxin Wang Yanming Shen Di He 16 11 0 15 Jun 2021
Evaluating Modules in Graph Contrastive Learning Ganqu Cui Y. Du Cheng Yang Jie Zhou Liang Xu Xing Zhou Lifeng Wang Zhiyuan Liu 23 4 0 15 Jun 2021
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond Jonathan Godwin Michael Schaarschmidt Alex Gaunt Alvaro Sanchez-Gonzalez Yulia Rubanova Petar Velivcković J. Kirkpatrick Peter W. Battaglia 41 60 0 15 Jun 2021
Training Graph Neural Networks with 1000 Layers Guohao Li Matthias Muller Guohao Li V. Koltun GNN AI4CE 51 235 0 14 Jun 2021
Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions Xuefeng Du Tian Bian Yu Rong Bo Han Tongliang Liu Tingyang Xu Wenbing Huang Yixuan Li Junzhou Huang NoLa 43 11 0 14 Jun 2021
Node Classification Meets Link Prediction on Knowledge Graphs Ralph Abboud .Ismail .Ilkan Ceylan 16 3 0 14 Jun 2021
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction Zhaocheng Zhu Zuobai Zhang Louis-Pascal Xhonneux Jian Tang GNN 33 300 0 13 Jun 2021
Graph Neural Networks with Local Graph Parameters Pablo Barceló Floris Geerts Juan L. Reutter Maksimilian Ryschkov 29 65 0 12 Jun 2021
TDGIA:Effective Injection Attacks on Graph Neural Networks Xu Zou Qinkai Zheng Yuxiao Dong Xinyu Guan Evgeny Kharlamov Jialiang Lu Jie Tang AAML 45 100 0 12 Jun 2021
Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs Jialin Dong Da Zheng Lin F. Yang Geroge Karypis GNN 14 36 0 11 Jun 2021
Graph Contrastive Learning Automated Yuning You Tianlong Chen Yang Shen Zhangyang Wang 24 451 0 10 Jun 2021
Adversarial Graph Augmentation to Improve Graph Contrastive Learning Susheel Suresh Pan Li Cong Hao Jennifer Neville AAML 26 336 0 10 Jun 2021
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings Matthias Fey J. E. Lenssen F. Weichert J. Leskovec GNN 23 133 0 10 Jun 2021
Automated Self-Supervised Learning for Graphs Wei Jin Xiaorui Liu Xiangyu Zhao Yao Ma Neil Shah Jiliang Tang SSL 31 76 0 10 Jun 2021
AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange Liang Zeng Jin Xu Zijun Yao Yanqiao Zhu Jian Li 38 1 0 10 Jun 2021
Do Transformers Really Perform Bad for Graph Representation? Chengxuan Ying Tianle Cai Shengjie Luo Shuxin Zheng Guolin Ke Di He Yanming Shen Tie-Yan Liu GNN 50 436 0 09 Jun 2021
Rethinking Graph Transformers with Spectral Attention Devin Kreuzer Dominique Beaini William L. Hamilton Vincent Létourneau Prudencio Tossou 46 508 0 07 Jun 2021
Formalizing Distribution Inference Risks Anshuman Suri David Evans MIACV AAML 25 4 0 07 Jun 2021
On Local Aggregation in Heterophilic Graphs Hesham Mostafa Marcel Nassar Somdeb Majumdar 18 4 0 06 Jun 2021
Graph Belief Propagation Networks Junteng Jia Cenk Baykal Vamsi K. Potluru Austin R. Benson GNN 19 3 0 06 Jun 2021
Graph Barlow Twins: A self-supervised representation learning framework for graphs Piotr Bielak Tomasz Kajdanowicz Nitesh Chawla SSL 21 135 0 04 Jun 2021
Learning from Counterfactual Links for Link Prediction Tong Zhao Gang Liu Daheng Wang Wenhao Yu Meng Jiang CML OOD 40 93 0 03 Jun 2021
Partial Graph Reasoning for Neural Network Regularization Tiange Xiang Chaoyi Zhang Yang Song Siqi Liu Hongliang Yuan Weidong (Tom) Cai OOD 14 2 0 03 Jun 2021
How Attentive are Graph Attention Networks? Shaked Brody Uri Alon Eran Yahav GNN 60 1,025 0 30 May 2021
Relational Graph Neural Network Design via Progressive Neural Architecture Search Ailing Zeng Minhao Liu Zhiwei Liu Ruiyuan Gao Jing Qin Qiang Xu 19 0 0 30 May 2021
On the Universality of Graph Neural Networks on Large Random Graphs Nicolas Keriven A. Bietti Samuel Vaiter 36 23 0 27 May 2021
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks Ruchi Puri David S. Kung G. Janssen Wei Zhang Giacomo Domeniconi ... Saurabh Pujar Shyam Ramji Ulrich Finkler Susan Malaika Frederick Reiss 32 228 0 25 May 2021
Heterogeneous Graph Representation Learning with Relation Awareness Le Yu Leilei Sun Bowen Du Chuanren Liu Weifeng Lv Hui Xiong 32 53 0 24 May 2021
A Robust and Generalized Framework for Adversarial Graph Embedding Jianxin Li Xingcheng Fu Hao Peng Senzhang Wang Shijie Zhu Qingyun Sun Philip S. Yu Lifang He 30 16 0 22 May 2021
Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework Junxiang Wang Hongyi Li Zheng Chai Yongchao Wang Yue Cheng Liang Zhao MQ 27 3 0 20 May 2021
Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks Huixuan Chi Yuying Wang Qinfen Hao Hong Xia GNN 24 11 0 18 May 2021